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Executive SummaryWith consumers and businesses spending ever more What is MongoDB?time connected to the Internet, telecoms can expectgrowing demand for their services. But demand In traditional relational databases like Oracle anddoesn’t always translate to profit, as competition, MySQL, data are stored in linked tables organizedcommoditization, operational complexity, and network into rows and columns. Each row is associated withinvestment costs threaten to turn telecommunications a unique entity, often a customer account, and eachproviders into low-margin ‘dumb pipes.’ column is associated with a field defining an attribute of the account. Separate tables store different typesMore than perhaps any other industry, telecommuni- of information about an account (e.g., mailing address,cations is disrupted every few years by market-shifting billing history), with common identifiers linking tablesinnovations. To compete, telecoms need to develop together. Schemas, or maps, that diagram thesenew services, and to do so rapidly, before their links and define allowable fields are locked in duringcompetitive advantage is neutralized. Telecoms need the database development period, and managed bytools that allow them to adapt to changing needs database administrators (DBAs), who must approvequickly and affordably, with the reliability they expect any changes. This approval process creates afrom their long-lived legacy systems. bottleneck for developers trying to create and modify applications quickly.MongoDB, the leading NoSQL database, allowstelecommunication companies to develop new MongoDB uses a more flexible data model. Aapplications quickly and adapt them as needs change. document database, MongoDB allows for varied dataIt is highly scalable, perfect for an age in which types and rapid addition of new fields. While entities incompanies are capturing exponentially increasing relational databases must pull information from fieldsvolumes of data. And in an environment buffeted by in multiple tables, a single MongoDB document canmany economic challenges, MongoDB’s total cost of store an entity’s entire information. These documentsownership can be orders of magnitude less than that can contain as many or as few fields as necessary.of traditional databases like Oracle.1 Creating new fields doesn’t necessarily require admin- 1 See the 10Gen White Paper, “A Total Cost of Ownership Comparison of MongoDB & Oracle.” http://www.10gen.com/sites/default/files/downloads/10gen.TCO%20-%20MongoDB%20vs.%20Oracle.pdf 1

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istrative approval. Developers can create new fields the original server. Machines can be simple commodityas they create new documents, write a script to servers found in cloud services like Amazon’s EC2.add the field to all documents or batch-populate No expensive purpose-built hardware needs to bedocuments with a new field when sending a request upgraded or replaced. Companies can thereforeto the database. Since new fields can be added ad quickly and cost-effectively scale their applicationshoc, MongoDB works well with unstructured, semi- in response to demand, and easily re-deploy systemstructured and polymorphic data—unlike relational resources as needs change. Sharding brings perfor-databases, which can’t easily store different types of mance benefits as well, as companies can place groupsdata and require data to be structured before they of documents on machines closer to the geographiccan be mapped. With MongoDB, notes from customer source of those documents so, for example, customersservice calls can be stored first, and organized later. in a particular region can access their user information more quickly.Because the documents in MongoDB are similar tothe ‘objects’ used in most modern applications and MongoDB provides many of the features that will beprogramming languages, developers find MongoDB familiar to users accustomed to relational databases.easy to work with. Documents are described in the MongoDB uses a rich query language for searchingJavascript Object Notation (JSON) format, familiar to the database and supports indexing of documents onusers of Javascript. Developers don’t have to spend secondary fields. MongoDB provides an interface formuch time learning MongoDB’s syntax, or mapping interacting directly with the database, and drivers fortheir application structure to the database structure. most popular programming languages, including Java,This contrasts sharply with relational databases. For C++, C#, PHP and Python. To provide the high level ofrelational databases, developers and database admin- uptime that users expect from relational databases,istrators must ensure that their database schemas are MongoDB supports the automated replication ofaligned across three layers: the application, the appli- database shards on up to 14 back-up servers andcation-database interface (object-relational map, or automated failover to back-ups when primaryORM) and the database itself. The need to create and servers fail.maintain three separate, but consistent, data mapscreates administrative drag. With MongoDB, there is no With users as varied as Viber, Disney and Cisco,need for separate data maps or approval processes for MongoDB has proven its versatility as a general-creating new fields. Developers can create new appli- purpose database. Unlike some other NoSQLcations rapidly, and revise and enhance them quickly. databases, MongoDB allows analytics tools to record and analyze changes to the database in real-time.The volume of data created by popular social, mobile There is none of the lag-time associated with batchand video applications is immense. As relational processing tools like Hadoop. MongoDB can be useddatabase deployments reach their processing and with a diverse set of applications, from contentstorage limits, companies are faced with the expensive management to data mining, allowing developers toand complex task of upgrading their purpose-built focus their time on application development, ratherservers and storage area networks (SANs). Upgrading than database maintenance and schema updates.servers often means several hours or even days ofdowntime. MongoDB, however, allows companies to With its flexible, simple and developer-friendly dataexpand their processing power and storage capacity model, MongoDB empowers organizations to be agile,easily across multiple off-the-shelf machines, on-site to act like startups. They can get new applications toor in the cloud, with no downtime. market quickly, and revise, upgrade and expand them as needs evolve. In many companies, administratorsWith MongoDB, large databases can be partitioned of relational databases limit the number of changesinto groups of documents, known as ‘shards.’ These that can be made to the database structure to one orshards are distributed across different machines, with two times per year. With MongoDB, there’s no need forboth processing and storage occurring separately from such limits. 2

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Telecoms Adapt to Slow Growth Customer Case StudiesTelecoms tackled the problem of ‘big data’ beforemany other industries. Telecoms implemented theoriginal operating support systems in the early 1970s Outside the Box: Capitalizing onas a way to automate and speed up the massive Online Videonumber of tasks they needed to do: taking orders, As consumers have watched increasing amounts ofassigning lines, configuring network components, video online, pay-TV providers have had to adapt.collecting payments and so on. They were some of the Many providers have pursued ‘TV Everywhere’ strat-early adopters of relational databases, with Bell Labs egies that enable their customers to watch contentpurchasing an Oracle machine as early as 1979, only a on devices other than their TVs. A few have pursuedyear after Oracle’s commercial launch. Billing support standalone Internet-based video services to competesystems and operating support systems from the ‘70s directly with Netflix, NOW TV, LOVEFiLM and otherallowed for mass automation, but rules had to be streaming video providers.hard-coded and data relationships were fixed. Gettingdifferent legacy systems to speak to each other remains A major pay-TV provider recently launched an onlinean ongoing problem for many telecoms. video site that allows users to subscribe on a monthly basis or order movies a la carte. Users can chooseToday, telecoms face different challenges. In mature from a catalogue of more than 1,500 films, and pause,markets, telecoms confront competition not only rewind or fast-forward programs easily. Users can markfrom companies offering similar technologies (e.g., films for future viewing, and automatically receivetwo wireless operators) but from companies offering recommendations for other films they might like.the same applications over different technologies(e.g., a landline and wireless operator), wholesale The provider chose MongoDB to power its systemoperators with different cost structures and nimble because of its flexibility and scalability. The companystartups offering competitive applications over the wanted a system that could support 70,000 concurrentInternet. Opportunities for new subscriber growth are users during peak hours, with users making constantlimited, with mobile penetration in most rich countries calls to the database to search, browse, rewind, pauseexceeding 100%, fixed-line subscriptions falling and and fast-forward films. The database also stores datapay-TV subscriptions flat in many countries. on where exactly in a film viewers pause watching so they can return to the content later.Telecoms are therefore turning to their existingsubscriber bases for revenue growth. They are The ease of adding new fields to documents inconsidering new revenue streams—like targeted adver- MongoDB permits developers to rapidly add newtising—and additional value-added services, like meta-tags to characterize films in a variety of ways,over-the-top video and consumer cloud storage, to alongside the traditional tags like actor, director andincrease their revenue per user. Even if these appli- genre. Over time, the recommendation engine becomescations cannot easily be monetized, they can help smarter, as it leverages a growing base of content,strengthen brand loyalty, reducing customer churn and meta-tags and information about user behavior.therefore increasing the lifetime value of subscribers. In the future, MongoDB’s support for mixed hierar-At the same time, increasing demands on telecoms’ chies will allow the provider to add new contentnetworks are creating a need for increased capital types like TV show collections and even live events.investment. To maintain margins, telecommuni- MongoDB’s ability to support documents nested insidecation service providers are looking for ways to reduce other documents means that developers won’t havetheir costs across all parts of the business, including to categorize individual episodes of TV shows at thenetwork operations, customer service and marketing. same level as standalone films. Users will be ableReducing customer acquisition costs is a particular to access a particular content type—for example, afocus of many rich world telecoms. football team’s season—and find programs organized in an intuitive way. 3

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Shared Experiences: Consumer Cloud viewing permissions, location data and timestamps.Storage as a Way to Reduce Churn Because adding new fields to the previous relational database system was such a time-consuming process,For years, a major European mobile operator was much of this type of data was previously stored in textahead of the curve in offering its subscribers the form or discarded. MongoDB, however, can automat-ability to store photos, music and video in the cloud. ically turn this data into new fields, so users can seeBut recently, the operator found that the MySQL where and when their photos or videos were taken.database it had built 13 years ago was reaching thelimits of scalability, and did not allow for the kind of By tying document storage to mobile subscrip-flexible access controls that users are accustomed to tions, the operator increases the stickiness of itson social networking sites. paid service and defends against churn in a market threatened by increasing competition. Improving theThe operator chose MongoDB to enable more flexible available features allows the operator to keep pacesharing. Subscribers can now share videos, photos, with standalone consumer cloud storage sites likephoto albums and mixed media albums with particular Dropbox, social networking sites and online photousers or categories of users. The content itself is album services.stored in a separate file system, while MongoDB isused to store metadata about the content, such as Featured Case Study How O2 Turned a Cost into an Opportunity O2 uses customer movement data to offer location-specific local offers. By necessity, wireless operators need to track the locations of their customers. Rational network investment hinges on knowing which cell sites require more capacity, or where more cell sites are needed. But where other operators saw a cost, O2, the United Kingdom’s leading wireless operator, saw an opportunity. What if you could get businesses to pay to offer your subscribers location-specific special offers? O2’s Priority Moments provides businesses a way to reach potential customers when they’re in the vicinity of one of their locations. O2 subscribers install a free mobile application and receive notifications about discounts and other special offers in their area. “Deals are delivered by location, so it’s quick and easy to find the offers and experiences they want,” said O2’s Andrew Pattinson. Traditional relational databases are ill-equipped to handle the complex volumes of data generated by millions of subscriber movements. Nor are they particularly adaptable if the application’s functionality needs to change. “Selecting MongoDB as our database platform was a no-brainer,” said Pattinson, “as the technology offered us the flexibility and scalability that we knew we’d need.” With more than 20 million subscribers, O2 required a database that could scale as usage grew. Deployed on Amazon Web Service’s cloud, the Priority Moments’ database can easily expand due to MongoDB’s support for database parti- tioning. MongoDB’s native geospatial support made MongoDB a natural fit, while MongoDB’s flexible data model will allow O2’s developers to tweak the application as subscribers’ and advertisers’ needs evolve. O2 was so satisfied with its experience with MongoDB that O2 and its parent company, Spain-based Telefonica, have started using MongoDB for other next-generation applications. Said Pattinson, “We’re very excited about MongoDB and look forward to more projects in the near future.” “Deals are delivered by location, so it’s quick and easy to find the offers and experiences they want.” -Andrew Pattinson, O2 4

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One-Stop Shop: A Universal Product Small Sensors, Big Data: Building aCatalog Across Multiple Channels Machine-to-Machine PlatformA large European mobile operator was finding it With the number of mobile subscriptions exceedingdifficult to maintain a consistent product catalog the size of the population in most mature markets,across all its channels: stores, telesales and the web. operators have looked to alternative sources forBecause of the lag time in updating the catalogs, a subscription growth. One highly promising area isuser could find an offer online, go into a store and machine-to-machine (M2M) communication in enter-find that the offer was not available yet. The operator prises, with estimates of future M2M connectionsneeded a system that allowed it to update offers once running into the tens of billions. Analyzing a constantand have those offers be instantaneously available to stream of readings from a large number of sensorsconsumers searching the catalog in any channel. They allows businesses to create efficiencies and identifyalso needed the ability to add and change products pain points in their infrastructures. But how do youquickly to respond to shifting market demands. enable companies to store, process, analyze and quickly act upon all this data?The operator initially chose Oracle as the databaseto power its new omnichannel product catalog. But While investigating database options for its M2Mafter spending more than $2 million and a year of enablement platform, a European mobile operatorwork, the operator found it was getting nowhere. The realized that using an Oracle database would bedatabase required an enormously complex schema, cost-prohibitive. The operator needed a system thatwith 250 tables required to describe a single product. could take in up to 10 billion sensor readings for aThe schema had to be reproduced in object-relational single customer, with each reading a separate recordmaps (the database-application interface) and the or document. But typical M2M use cases, such asapplication itself—undermining the original goal of fleet tracking systems for shipping companies, do notdeveloping a catalog that could be updated quickly. generate enough return to justify the large investmentOracle simply could not cope with the variations of required for an Oracle system that could handle thepayment options, devices, contract lengths, bolt-on desired data volumes.services and bundles the provider was offering. The operator chose MongoDB due to its lower totalHowever, MongoDB’s highly flexible data model and cost of ownership, flexible data model, scalability andeconomical approach to licensing allowed the operator support for real-time analytics. The beta customer isto develop a true omnichannel product catalog within a power company collecting readings from electricsix months and for a substantially smaller investment. meters every few minutes, eliminating the need toThe product catalog includes an array of prepaid and send out technicians and allowing the company topostpaid products, a growing selection of devices keep a closer eye on household-level usage in its(smartphones, tablets, wireless modems, SIMs) and distribution network. MongoDB’s support for real-timebolt-ons, such as data top-ups and international calling analytics allows the customer to set up alerts thatpackages. Different product types are organized in can be triggered when specified performance ordifferent hierarchies, and some products are simulta- utilization benchmarks are breached. MongoDB’s flexi-neously available in different sections of the site. In bility will also allow the operator to easily adapt theaddition, the operator has found it easy to add new platform for other types of sensor readings, such asproduct detail to product listings, such as specifica- temperature, speed and acceleration. And MongoDB’stions and regulatory-required safety notifications. scalability permits the platform to grow as more customers use the operator for M2M solutions, and as their needs grow. 5

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All in One Place: Know Your Customer Like Yourself:A True Subscriber Identity Customer Sentiment AnalysisManagement System UberVu, a social media analytics company, usesOver a customer’s lifetime, operators collect MongoDB to aggregate and analyze data from socialenormous amounts of data about their subscribers: networks for clients seeking insight into customerbilling histories, usage patterns, total usage, location sentiment on their products. Mentions of particular(for mobile operators), contract changes, service terms are annotated with pertinent data, such ascall histories and more. But a patchwork of legacy source (Twitter, Facebook, etc.), language, sentimentsystems, some decades old, collects this data in and time, and indexed in MongoDB. UberVu can easilydifferent databases, many of which don’t commu- filter these streams by attribute (language, gender, etc.)nicate with each other. To monetize this data and to produce segmented cuts on customer sentiment.improve internal operations, operators need a single MongoDB’s flexibility and scalability allows UberVu tosystem that is scalable and flexible enough to incor- add new sources and sentiment attributes over time,porate new types of data. and grow its storehouse of data as social networking use grows.A major wireless operator chose MongoDB as thedatabase for its subscriber identity management Telecommunications companies looking for insightsystem. Trying to aggregate customer data from a into their products can use MongoDB in a similar way.variety of systems was proving a bottleneck for devel- They can aggregate data from social networks, blogs,opers, who had to create numerous object-relational bulletin boards and media websites to answer toughmaps to get their applications to read from existing marketing questions, such as, are available downloadrelational databases. The operator’s new person- speeds affecting brand perception? MongoDB can helpalization server will aggregate data from dozens reduce the lag-time and expense involved in tradi-of systems in one place, eventually allowing both tional market research, by greatly reducing the needcustomers and internal personnel the ability to see for focus groups and customer surveys. MongoDB’sall data about a customer in a single location. ability to support rapid customer sentiment analysis allows companies to change course quickly if marketingAn improved subscriber identity management system campaigns prove ineffective, as well as anticipateimproves call center efficiency by reducing the amount emerging customer needs more rapidly. MongoDB’sof time customer service representatives need to pull support for varied data types allows telecoms to storedata on customers. MongoDB’s support for real-time a mix of external and internal data (customer serviceanalytics enables a live dashboard that shows trending calls, corporate website usage history, etc.), andcustomer service issues, which can help customer determine how best to annotate, analyze and useservice representatives determine whether customer the data at a later date.complaints are an isolated issue or part of a largerpattern. This complete view of a customer’s needs willimprove customer satisfaction and increase retention.A single source of customer data also allows devel-opers to build business intelligence systems morerapidly. Licenses to access these systems can be soldto retailers and others looking for data on subscribers’movements and Internet usage. 6

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MongoDB:Speed, Size, StabilityMongoDB enables telecoms to expand their customerbases, increase their revenue per user and improvetheir customer acquisition and retention. MongoDBdoesn’t require expensive licenses or proprietaryhardware, making it a natural fit for greenfield deploy-ments with unknown demand, like geo-targetedmobile advertising. Its cost-effective scalability andquick time-to-market makes it equally suitable totime-sensitive company-wide deployments, like anomnichannel product catalog. And its flexible datamodel provides companies with the agility to changeapplications like an M2M platform in response tocustomer demand. In addition, its support for real-timeanalytics makes it a great tool for improving internaloperations, from customer sentiment analysis toincreasing call center efficiency.For much of the last decade, telecoms have felt leftbehind by hardware and software vendors in the racefor innovation, hamstrung by their reliance on legacysystems. With its agility and scalability, MongoDBallows telecoms to couple the resources of a multina-tional with the speed of a startup. 7